The availability of small high accuracy image sensors has led to a proliferation of small and portable cameras in a wide range of different devices from security systems, to doorbells, to vehicle safety system and then smart phones, tablets, computers, etc. These cameras are combined with processors to provide extensive image processing, some in real time. The image processing opens up a wide range of new functions not previously available
Median filtering is a foundation of or a part of many image processing systems. Median filtering is found as a component in many imaging and vision systems, such as computer vision for face or gesture recognition and in computational photography. It is also used in image enhancement, such as image de-noising systems, adaptive histogram equalization, etc.
Median filtering sorts the set of pixel intensity or brightness values to which it is applied and returns a value that ranks exactly at the midpoint or median of the input values. In many cases, median filtering is applied to an entire image using a sliding window that slides across the image until it has covered every pixel. As a result of sorting every pixel, the complexity of median filtering is associated with the number of input pixels. Many median filter methods are applied to small size input data sets such as 3×3 image windows. While a smaller window makes each window easier and faster to compute, many more smaller windows are required in order to filter an entire window than larger windows. In addition, for some purposes a larger window is necessary to obtain a desired filter effect.